The AI-native security platform

Security review that thinks like an attacker.

One agent reviews your code, secrets, dependencies, and cloud the way a senior security engineer would — tracing real data flows, chaining attack paths, and proving what’s exploitable. Everything else is deleted before it reaches your team.

Connect GitHub — free →Watch the agent hunt
No credit card · Public repos always free
users.controller.ts1 CRITICAL
38router.get('/users', async (req, res) => {
39const id = req.query.id
SOURCE
40const query = buildQuery(id)
41const rows = await db.raw(query)
SINK
42res.json(rows)
43})
Reading users.controller.ts · 312 routes
req.query.iddb.raw()tainted
Building PoC · ?id=1' UNION SELECT token…
CONFIRMED · SQL INJECTION94%
found·verified·proven— across every repository
The architecture

Four engines for recall.
One agent for judgment.

Detection engines surface everything. The agent decides what’s real — and only verified, exploitable findings reach your team.

Recall
651 raw candidates
Judgment
adversarially verified
Proof
3 verified findings
Code analysis
taint · source → sink
312
Secret detection
history-deep · live
88
Dependencies
CVE & advisory
214
IaC analysis
misconfig + graph
37
The Zolt agent
analyzing 651 candidates
648 suppressed · deleted
3verified findings
Evidence + proof of concept
One PR review, diff-scoped
Worst-first posture board
Severity by real impact
How the agent reasons

Five phases. The same loop a human runs.

01

Comprehend

Reads the repo and builds a model of the application.

02

Map the surface

Finds every route, entry point, and trust boundary.

03

Trace data flows

Follows untrusted input source → sink, across files.

04

Investigate

Chains findings into multi-step attack paths.

05

Adversarial verify

Tries to kill every finding. Only survivors ship.

Coverage

Four problems. One hunter.

◇ CODE
SAST

Your scanner can’t read code. Attackers can.

The agent models your architecture and trust boundaries, traces input source → sink across files, and proves logic, auth, and injection flaws — each with a PoC.

◇ SECRETS

That key you deleted last year? It’s still there.

Every commit on every branch — not just HEAD. Each secret is live-verified against the provider and flagged LIVE if it still works.

◇ OPEN SOURCE
SCA

One bad package out of 214 is still a breach.

npm, PyPI, Go, Cargo, and Maven — transitive deps included. Full advisory context, and the exact version that fixes it, re-checked 24/7.

◇ INFRASTRUCTURE
IaC

Three “medium” misconfigs. One critical breach.

Terraform, Kubernetes, Docker, and CloudFormation. Resource-graph reasoning chains multi-hop paths from a public endpoint to your data.

Where you work

Reviews every pull request. Like a teammate.

Install the GitHub App once — no YAML, no CI rewrites. Every PR gets a diff-scoped review before it merges. A clean PR gets silence, not a sticker.

Scoped to the diff — fast enough to sit in the merge path
One consolidated comment, verified findings only
Source-to-sink trace right in the review
Add user lookup endpoint #1421CRITICAL
zolt-security bot · just now
SQL injection via unsanitized id parameter
req.query.iddb.raw(query)users.controller.ts:42

The id parameter flows unmodified into a string-built query. No parameterization; reachable unauthenticated. PoC attached.

caught before merge · re-runs on every push
4
security domains, one agent
5
reasoning phases per finding
100%
of git history scanned
24/7
dependency re-scans
Why switch

Legacy scanners create queues.
Zolt creates proof.

Rule-based scanners
Zolt
Signal
A queue of pattern matches someone triages by hand.
Verified findings, ranked by what’s actually exploitable.
Context
Single-file snippets with no idea where the data came from.
Cross-file traces, attack-path chains, a model of your app.
Coverage
Four separate tools for code, secrets, deps, and infra.
One agent across all four — findings that connect across layers.
Trust
Hundreds of findings; the team learns to ignore the bot.
Few findings, each with evidence and a proof of concept.
Standards-mapped:◇ OWASP Top 10◇ CWE◇ CVE◇ GHSA◇ CVSS
FAQ

Questions,
answered.

How is this different from a normal SAST scanner?+

Rule-based scanners pattern-match line by line — great recall, zero judgment. Zolt runs those engines for coverage, then an agent reads your code like an engineer: it models the app, traces real data flows, and adversarially re-checks every candidate before you see it. Recall without the noise.

What happens to my code?+

Each scan clones your repo into an ephemeral, isolated environment that exists only for the audit and is destroyed afterward. Access is through a GitHub App you control — you pick exactly which repos Zolt sees, and you can revoke it anytime.

Will it spam my pull requests?+

No. Zolt posts one consolidated review per pull request, scoped to the diff, containing only verified findings. If your PR is clean, it stays out of the way.

How do you keep false positives out?+

Every candidate goes through a dedicated adversarial pass whose default assumption is “this is a false positive” — it actively tries to kill the finding by re-reading the code. Only survivors ship, each with a confidence score, evidence chain, and PoC.

Ship secure code, with proof.

Connect GitHub and get your first verified findings in minutes — evidence and proof of concept included.

Get started free →Watch the agent again
No credit card · 2-minute setup · Revoke access anytime